modelledger
AI agents vs workflows: differences, examples and when to use each
Compare AI agents with fixed workflows using support and document-processing examples. Choose the simplest system you can test, control and recover.
The journal.
Clear thinking for the work in front of you.
9 stories
Claude usage limits: why Pro runs out and when limits reset
Understand Claude Pro session and weekly limits, where to check your reset time, and what to record before paying for more usage.
n8n vs Make pricing: compare executions, credits and real costs
Compare n8n executions with Make credits using a worked example. Include AI usage, retries and maintenance before choosing an automation plan.
The best AI model is the one that passes your test.
A practical framework for comparing AI tools on real work, with a reusable scorecard and a cost-per-accepted-result calculation.
Chat subscription or API: which fits the job?
Compare interactive AI tools and programmable workflows by control, billing, repeatability, and operational needs.
The AI cost that matters: one accepted result.
A worked example of why the cheaper API bill can produce the more expensive workflow once acceptance and review time enter the calculation.
Valid JSON is only the start of a reliable AI workflow.
A practical checklist for turning AI-generated fields into usable records: schema checks, source evidence, failure handling, and a small pilot.
From customer reviews to a useful AI report.
A repeatable review-analysis workflow that preserves source evidence and makes uncertain classifications visible.
What does an AI workflow actually cost?
Input tokens are only part of the bill. A clear way to estimate output, retries, tools, and human review before you scale.
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